{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_no = 10\n",
    "old_sensor_01_x = pd.read_csv(open('../../刀具剩余寿命预测_旧数据/raw_data/train_qLua/01/Sensor/%d.csv'%csv_no))\n",
    "new_sensor_01_x = pd.read_csv(open('../../刀具剩余寿命预测_新数据/raw_data/train_add/01/Sensor/%d.csv'%csv_no))\n",
    "final_sensor_01_x = pd.read_csv('../final_test_data/01/Sensor/%d.csv'%csv_no)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# old_sensor_01_x.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vibration_1</th>\n",
       "      <th>vibration_2</th>\n",
       "      <th>vibration_3</th>\n",
       "      <th>current</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.548800e+06</td>\n",
       "      <td>1.548800e+06</td>\n",
       "      <td>1.548800e+06</td>\n",
       "      <td>1.548800e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.127673e-02</td>\n",
       "      <td>-9.765987e-03</td>\n",
       "      <td>1.219620e-02</td>\n",
       "      <td>-3.286870e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.117028e+00</td>\n",
       "      <td>1.729320e+00</td>\n",
       "      <td>2.053379e+00</td>\n",
       "      <td>3.503534e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.794737e+01</td>\n",
       "      <td>-1.585809e+01</td>\n",
       "      <td>-1.433197e+01</td>\n",
       "      <td>-5.840641e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-1.216151e+00</td>\n",
       "      <td>-9.849971e-01</td>\n",
       "      <td>-1.281484e+00</td>\n",
       "      <td>-3.532266e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.991889e-02</td>\n",
       "      <td>1.529737e-03</td>\n",
       "      <td>9.736386e-03</td>\n",
       "      <td>-4.090260e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.258184e+00</td>\n",
       "      <td>9.804947e-01</td>\n",
       "      <td>1.303889e+00</td>\n",
       "      <td>3.463058e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.667672e+01</td>\n",
       "      <td>1.650172e+01</td>\n",
       "      <td>2.608433e+01</td>\n",
       "      <td>5.738468e+01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        vibration_1   vibration_2   vibration_3       current\n",
       "count  1.548800e+06  1.548800e+06  1.548800e+06  1.548800e+06\n",
       "mean   3.127673e-02 -9.765987e-03  1.219620e-02 -3.286870e-01\n",
       "std    2.117028e+00  1.729320e+00  2.053379e+00  3.503534e+01\n",
       "min   -1.794737e+01 -1.585809e+01 -1.433197e+01 -5.840641e+01\n",
       "25%   -1.216151e+00 -9.849971e-01 -1.281484e+00 -3.532266e+01\n",
       "50%    1.991889e-02  1.529737e-03  9.736386e-03 -4.090260e-01\n",
       "75%    1.258184e+00  9.804947e-01  1.303889e+00  3.463058e+01\n",
       "max    1.667672e+01  1.650172e+01  2.608433e+01  5.738468e+01"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_sensor_01_x.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmp = new_sensor_01_x['vibration_1']\n",
    "std = tmp.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc470825470>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(new_sensor_01_x.loc[:1000, 'vibration_1'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vibration_1</th>\n",
       "      <th>vibration_2</th>\n",
       "      <th>vibration_3</th>\n",
       "      <th>current</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.536000e+06</td>\n",
       "      <td>1.536000e+06</td>\n",
       "      <td>1.536000e+06</td>\n",
       "      <td>1.536000e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.428891e-02</td>\n",
       "      <td>-2.588341e-03</td>\n",
       "      <td>2.045114e-02</td>\n",
       "      <td>-1.804296e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.985655e+00</td>\n",
       "      <td>1.857422e+00</td>\n",
       "      <td>2.186877e+00</td>\n",
       "      <td>1.410648e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.622503e+01</td>\n",
       "      <td>-1.644158e+01</td>\n",
       "      <td>-1.501692e+01</td>\n",
       "      <td>-2.359086e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-1.150882e+00</td>\n",
       "      <td>-1.049883e+00</td>\n",
       "      <td>-1.354535e+00</td>\n",
       "      <td>-1.423987e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.601900e-02</td>\n",
       "      <td>1.378700e-02</td>\n",
       "      <td>2.170800e-02</td>\n",
       "      <td>-2.243950e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.209142e+00</td>\n",
       "      <td>1.061602e+00</td>\n",
       "      <td>1.394897e+00</td>\n",
       "      <td>1.385034e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.467366e+01</td>\n",
       "      <td>1.400445e+01</td>\n",
       "      <td>1.673281e+01</td>\n",
       "      <td>2.334567e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        vibration_1   vibration_2   vibration_3       current\n",
       "count  1.536000e+06  1.536000e+06  1.536000e+06  1.536000e+06\n",
       "mean   3.428891e-02 -2.588341e-03  2.045114e-02 -1.804296e-02\n",
       "std    1.985655e+00  1.857422e+00  2.186877e+00  1.410648e+00\n",
       "min   -1.622503e+01 -1.644158e+01 -1.501692e+01 -2.359086e+00\n",
       "25%   -1.150882e+00 -1.049883e+00 -1.354535e+00 -1.423987e+00\n",
       "50%    2.601900e-02  1.378700e-02  2.170800e-02 -2.243950e-02\n",
       "75%    1.209142e+00  1.061602e+00  1.394897e+00  1.385034e+00\n",
       "max    1.467366e+01  1.400445e+01  1.673281e+01  2.334567e+00"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_sensor_01_x.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmp = final_sensor_01_x['vibration_1']\n",
    "std = tmp.std()\n",
    "# (tmp/std).mean()\n",
    "# plt.plot((tmp/std).loc[:1000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc470804e48>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(final_sensor_01_x.loc[:1000, 'vibration_1'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
